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Method for automatically positioning head shadow positioning point

A cephalometric and automatic positioning technology, which is applied in neural learning methods, instruments, biological neural network models, etc., can solve problems affecting the accuracy of analysis work and achieve the effect of automatic detection

Pending Publication Date: 2021-07-02
TIANJIN UNIV
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Problems solved by technology

Cephalometric landmark detection is a key part of X-ray cephalometric measurement, which greatly affects the accuracy of analysis work

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  • Method for automatically positioning head shadow positioning point
  • Method for automatically positioning head shadow positioning point
  • Method for automatically positioning head shadow positioning point

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Embodiment Construction

[0031] Aiming at the problem of landmark detection in cephalometric analysis, the present invention proposes to adopt a deep learning algorithm, and builds a fully automatic detection algorithm framework by establishing a cascade regression network. The core idea is a coarse-to-fine positioning process, combined with a cascaded model of two regression tasks as a local feature point detector, and finally obtains the feature point positioning results to realize the automatic detection of anatomical landmarks.

[0032] The calibration of cephalometric landmarks is an extremely important link in cephalometric analysis, and the accuracy of landmark detection is related to how doctors formulate treatment plans for patients. In orthodontics, there are about 90 cephalometric landmarks, of which dozens are commonly used, and different measurement methods require different landmarks for calculation. figure 1 It is an X-ray cephalometric film taken by a head locator, in which the red dot...

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Abstract

The invention relates to the technical field of computer vision, medical image processing, key point detection and the like, and provides a method for automatically positioning a head shadow positioning point. The method for automatically positioning a head shadow measurement mark point comprises the following steps: step 1, preparing data of an X-ray head side position film; step 2, acquiring marking points of doctors in the training set, and performing feature selection; step 3, training a first-layer regression tree model, updating positions of all mark points once every time the first-level regression tree model passes through a cascade regression device to enable the mark points to be closer to the mark points, and calculating a difference value between a current shape and a real shape as a residual error; step 4, training a regression device of each stage in the cascade network; and step 5, updating the current shape to be the current shape plus the residual error, and constructing a cascade residual error regression tree until splitting to leaf nodes. The method is mainly applied to the occasion of automatically positioning the head shadow survey mark point.

Description

technical field [0001] The invention relates to technical fields such as computer vision, medical image processing, and key point detection. Taking cephalometric analysis in stomatology as an application scenario, a deep learning method is used to realize automatic positioning of anatomical feature points in cephalometric films. Specifically, it relates to a method for automatically locating cephalometric marker points. Background technique [0002] With the improvement of living standards in recent years, people's attention to oral health has greatly increased, and a healthy and tidy set of teeth has become the pursuit of more and more people. Through orthodontics, patients can improve their facial shape and occlusal relationship, and also help maintain periodontal health, so as to improve their appearance and protect their health. Orthodontics is actually the correction of teeth to solve the problem of malocclusion and achieve the effect of satisfying the normal occlusal ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/32G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V10/245G06V10/40G06N3/045G06F18/214
Inventor 魏建国石启萌王璐
Owner TIANJIN UNIV
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